Lithospheric thickness records tectonic evolution by controlling metamorphic conditions.

The lithosphere, as the outermost solid layer of our planet, preserves a progressively more fragmentary record of geological events and processes from Earth's history the further back in time one looks. Thus, the evolution of lithospheric thickness and its cascading impacts in Earth's tectonic system are presently unknown. Here, we track the lithospheric thickness history using machine learning based on global lithogeochemical data of basalt. Our results demonstrate that four marked lithospheric thinning events occurred during the Paleoarchean, early Paleoproterozoic, Neoproterozoic, and Phanerozoic with intermediate thickening scenarios. These events respectively correspond to supercontinent/supercraton breakup and assembly periods. Causality investigation further indicates that crustal metamorphic and deformation styles are the feedback of lithospheric thickness. Cross-correlation between lithospheric thickness and metamorphic thermal gradients records the transition from intraoceanic subduction systems to continental margin and intraoceanic in the Paleoarchean and Mesoarchean and a progressive emergence of large thick continents that allow supercontinent growth, which promoted assembly of the first supercontinent during the Neoarchean.

Reconstructing Earth's atmospheric oxygenation history using machine learning.

Reconstructing historical atmospheric oxygen (O2) levels at finer temporal resolution is a top priority for exploring the evolution of life on Earth. This goal, however, is challenged by gaps in traditionally employed sediment-hosted geochemical proxy data. Here, we propose an independent strategy-machine learning with global mafic igneous geochemistry big data to explore atmospheric oxygenation over the last 4.0 billion years. We observe an overall two-step rise of atmospheric O2 similar to the published curves derived from independent sediment-hosted paleo-oxybarometers but with a more detailed fabric of O2 fluctuations superimposed. These additional, shorter-term fluctuations are also consistent with previous but less well-established suggestions of O2 variability. We conclude from this agreement that Earth's oxygenated atmosphere may therefore be at least partly a natural consequence of mantle cooling and specifically that evolving mantle melts collectively have helped modulate the balance of early O2 sources and sinks.

The Deep-Time Digital Earth program: data-driven discovery in geosciences.

Current barriers hindering data-driven discoveries in deep-time Earth (DE) include: substantial volumes of DE data are not digitized; many DE databases do not adhere to FAIR (findable, accessible, interoperable and reusable) principles; we lack a systematic knowledge graph for DE; existing DE databases are geographically heterogeneous; a significant fraction of DE data is not in open-access formats; tailored tools are needed. These challenges motivate the Deep-Time Digital Earth (DDE) program initiated by the International Union of Geological Sciences and developed in cooperation with national geological surveys, professional associations, academic institutions and scientists around the world. DDE's mission is to build on previous research to develop a systematic DE knowledge graph, a FAIR data infrastructure that links existing databases and makes dark data visible, and tailored tools for DE data, which are universally accessible. DDE aims to harmonize DE data, share global geoscience knowledge and facilitate data-driven discovery in the understanding of Earth's evolution.

A high-resolution summary of Cambrian to Early Triassic marine invertebrate biodiversity.

One great challenge in understanding the history of life is resolving the influence of environmental change on biodiversity. Simulated annealing and genetic algorithms were used to synthesize data from 11,000 marine fossil species, collected from more than 3000 stratigraphic sections, to generate a new Cambrian to Triassic biodiversity curve with an imputed temporal resolution of 26 ± 14.9 thousand years. This increased resolution clarifies the timing of known diversification and extinction events. Comparative analysis suggests that partial pressure of carbon dioxide (Pco2) is the only environmental factor that seems to display a secular pattern similar to that of biodiversity, but this similarity was not confirmed when autocorrelation within that time series was analyzed by detrending. These results demonstrate that fossil data can provide the temporal and taxonomic resolutions necessary to test (paleo)biological hypotheses at a level of detail approaching those of long-term ecological analyses.

Quantitative Analysis of Iron and Silicon Concentrations in Iron Ore Concentrate Using Portable X-ray Fluorescence (XRF).

As a technique capable of rapid, nondestructive, and multi-elemental analysis, portable X-ray fluorescence (pXRF) has applications to mineral exploration, environmental evaluation, and archaeological analysis. However, few applications have been conducted in the smelting industry especially when analyzing the metal concentration in ore concentrate samples. This research analyzed the effectiveness of using pXRF in determining the metal concentration in Fe concentrate. For this proof of concept study, Fe ore samples dominated by Fe and Si were collected from the Northeastern University Mineral Processing Laboratory (Shenyang, China) and directly analyzed using pXRF, laboratory-based XRF, and titration methods. The compactness (density) of the ore concentrate was found to have very little effect on pXRF readings. The pXRF readings for Fe and Si were comparative to laboratory-based XRF results. Based on the strong correlations between the pXRF and XRF results (Fe: R2 > 0.99, Si: R2 > 0.96), linear calibrations were adopted to improve the accuracy of pXRF readings. Linear regression equations derived from the relations between XRF results and pXRF results of 21 Fe ore concentrate samples were used to calibrate the pXRF, and then validation was performed on five additional samples. Results from this preliminary study suggest that ordinary least squares (OLS) regression improves the accuracy dramatically, especially for Fe with relative errors (REs) decreasing to 0.03%-3.27% from 4.26%-8.32%. Consequently, pXRF shows strong promise for rapid, quantitative analysis of Fe concentration in Fe ore concentrate. Based on the results obtained in this study, a larger, more comprehensive study is warranted to confirm the results obtained.

Rapid in situ determination of heavy metal concentrations in polluted water via portable XRF: Using Cu and Pb as example.

In this research, the effectiveness of using portable X-ray fluorescence (pXRF), with the help of waterproof film, to determine the concentration of the heavy metals Cu and Pb in polluted water was assessed through indoor and field studies. The effects of the thickness of the film and the distance between the instrument and sample were also evaluated. The penetration depth of X-rays in water was found to be between 2 mm and 4 mm, and a water sample of at least 4 mm in depth was thus suggested. The minimum detectable concentration for Cu was ca. 21 ppm and ca. 28 ppm for Pb. Based on the indoor study, the pXRF results were found to be comparable with the certified concentrations of prepared solutions (R2 > 0.99 for both Cu and Pb). The field pXRF readings also showed a good linear correlation with the corresponding laboratory results (R2 > 0.95 for Cu). The calibration formula derived from indoor analysis was used to correct the field pXRF results and effectively improved the accuracy. Consequently, pXRF has the potential to be applied to the analysis of polluted waters with relatively high concentrations (e.g., >20-30 ppm Cu), which would benefit the in situ monitoring of water pollution caused by heavy metals.